Zgouz A. auteur aut IRD Heran D. auteur aut IRD Barthès Bernard auteur aut IRD Bastianelli D. auteur aut IRD Bonnal L. auteur aut IRD Baeten V. auteur aut IRD Lurol S. auteur aut IRD Bonin M. auteur aut IRD Roger J. M. auteur aut IRD Bendoula R. auteur aut IRD Chaix G. auteur aut IRD text journalArticle eng text/pdf reformatted digital access In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log(10) (1/Reflectance)], and another file for reference data, in order to assess the potential of the micro spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open ac cess dataset could also be used to test new chemometric methods, for training, etc. specialized Micro-spectrometers Handheld devices Visible-near infrared spectroscopy chemometrics sugarcane 076 020 31 106013 [6 ] 2020 2352-3409 https://www.documentation.ird.fr/hor/fdi:010079738 10.1016/j.dib.2020.106013 2352-3409 [F B010079738] https://www.documentation.ird.fr/hor/fdi:010079738 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers20-10/010079738.pdf IRD - Base Horizon / Pleins textes 2020-11-12 2025-02-24 fdi:010079738 fre